Number of hours
- Lectures 0
- Projects 32.0
- Tutorials 0
- Internship 0
- Laboratory works 0
- Written tests 0
ECTS
ECTS 4.0
Goal(s)
This project is interested in the implementation of deep learning algorithms applied to images on GPU processor.
The objective is to illustrate an approach of adequacy between algorithm and architecture that is necessary for an efficient implementation. Industrial flows of development are used in this teaching.
Content(s)
The project takes place in two stages:
- Study of the convolutional neural network with its database experimented with standard tools (Keras ...)
- C / CUDA implementation on CPU / GPU of the different CNN layers with optimization of the implementation on GPU
Prerequisites
Test
Semester 9 - The exam may be taken in french or in english 
during the last project session, there will be an oral presentation of the work carried out. A 15-20 page project report is also produced.
Rapport : 100%
Additional Information
Semester 9 - This course is given in english only
Course list
Curriculum->Master->Semester 9
Curriculum->Double-Diploma Engineer/Master->Semester 9
Bibliography
CUDA programming guide, Nvidia